Datasets of search_TPS - A Bioinformatics Tool for Efficient Retrieval of High-Confidence Terpene Synthases (TPS) and Application to the Identification of TPS in Coffea and Quillaja
| Main Authors: | Domingues, Douglas S, Oliveira, Liliane S, Lemos, Samara, Barros, Gian, Ivamoto-Suzuki, Suzana T |
|---|---|
| Format: | info dataset Journal |
| Bahasa: | eng |
| Terbitan: |
Springer
, 2021
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/4542419 |
Daftar Isi:
- Here we have support data for the chapter "A Bioinformatics Tool for Efficient Retrieval of High-Confidence Terpene Synthases (TPS) and Application to the Identification of TPS in Coffea and Quillaja". We include here the guide tree that was used for the development of TPS specific HMM profiles (PB_all.pdf). We detail here the datasets of cured TPS genes we used for tool validation (from Arabidopsis thaliana, Solanum lycopersicum and Setaria italica), in CaseStudy1.xlsx file. We also describe the TPS genes identified in Coffea canephora, Coffea eugenioides, Coffea arabica and Quillaja saponaria (ValidatioTablev1.xlsx). In the case of Q. saponaria, we reassembled the transcriptome based on public RNA-seq data (Bioproject PRJEB8056). We followed the protocol "Best Practices for De Novo Transcriptome Assembly with Trinity" (Published on Tue 29 September 2020 By Adam Freedman, Nathan Weeks [https://informatics.fas.harvard.edu/best-practices-for-de-novo- transcriptome-assembly-with-trinity.html]) and obtained a transcriptome assembly with the following statistics: Total trinity 'genes': 36582 Total trinity transcripts: 47608 Median contig length: 547 Average contig: 787.36 The transcripts were annotated using the Trinotate v3.2.1 pipeline (http://trinotate.github.io). All of the annotated peptide sequences (Trinity_Qsap_pep.fasta) were used as input for search_TPS. search_TPS (search_TPS_Tutorialvf.pdf) is freely available at https://github.com/liliane-sntn/TPS. To report bugs, to ask for help and to give any feedback, please contact Liliane S. Oliveira (liliane.sntn@gmail.com) or Douglas S. Domingues (douglas.domingues@unesp.br).
- This work was partially financed by the São Paulo State Research Foundation (FAPESP) (grants number 2016/10896-0; 2017/01455-2, 2019/15477-3). SMCL receives a CAPES fellowship (Finance Code - 001). DSD is a CNPq research productivity fellow (#312823/2019-3). Douglas S. Domingues, Liliane S. Oliveira and Suzana T. Ivamoto-Suzuki contributed equally to this work.